DETERMINING A CLINICAL PARAMETER VIA EVALUATION OF SEQUENTIAL MEDICAL IMAGES

    公开(公告)号:US20250069216A2

    公开(公告)日:2025-02-27

    申请号:US18015021

    申请日:2021-07-07

    Abstract: Systems and methods are provided for determining a clinical parameter via evaluation of sequential medical images. A sequence of at least three medical images for a patient are captured at a scanner. A set of at least two difference images are generated from the sequence of at least three medical images. Each difference image represents a difference in content between two adjacent images in the sequence of at least three medical images. The set of at least two difference images are provided to a predictive model. The predictive model includes an artificial neural network having at least one convolutional layer. A clinical parameter for the patient is determined at the predictive model from at least the set of at least two difference images.

    ANTAGONISTIC ANTI-TUMOR NECROSIS FACTOR RECEPTOR SUPERFAMILY POLYPEPTIDES

    公开(公告)号:US20250066494A1

    公开(公告)日:2025-02-27

    申请号:US18948807

    申请日:2024-11-15

    Abstract: Described are antagonistic TNFR2 polypeptides, such as antibodies and antigen-binding fragments thereof, and the use of these polypeptides to inhibit the proliferation of regulatory T cells (T-regs) and/or myeloid-derived suppressor cells (MDSCs), to expand T effector cell populations or function, and to reduce the proliferation of, or directly kill, tumor cells, such as tumor cells that express TNFR2 antigen. The polypeptides, such as antibodies and antigen-binding fragments thereof, are TNFR2 antagonists, such as dominant TNFR2 antagonists. The polypeptides can be used to suppress the T-reg- or MDSC-mediated deactivation of tumor reactive T lymphocytes, expand populations of tumor-reactive cytotoxic T cells, and/or to directly kill TNFR2+ tumor cells. The antagonistic TNFR2 polypeptides described herein can be used to treat a wide variety of cancers and infectious diseases.

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